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-.. Caisar documentation master file, created by
+.. CAISAR documentation master file, created by
    sphinx-quickstart on Thu Jun 16 11:14:48 2022.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to Caisar's documentation!
-**********************************
+CAISAR documentation
+====================
+
+.. image:: _static/media/caisar_logo.png
+
+*Written in november 2022*
+
+CAISAR is an open-source platform for the Characterization of Artificial
+Intelligence Safety And Robustness.
+Its expressive modelling language allows the description of
+a wide variety of specifications to enforce on a machine learning system.
+The specification is then decomposed into subproblems that
+are then sent to specialized provers.
+CAISAR aims to be component-agnostic: it can model and assess the trustworthiness of an hybrid artificial intelligence systemthat mixes symbolic and data-driven approaches.
 
-CAISAR (Characterizing AI Safety And Robustness) is a platform
-under active development at CEA LIST, aiming to provide a
-wide range of features to characterize the robustness of
-artificial intelligence based software.
 It is available as a free software under the LGPLV2.1
-license. Code is hosted at
-https://git.frama-c.com/pub/caisar.
+license. The code is is hosted in our `gitlab instance
+<https://git.frama-c.com/pub/caisar>`_.
+
+Architecture and components
+---------------------------
+
+CAISAR relies on the `Why3 verification platform <https://why3.lri.fr/>`_
+to provide both the basis of the specification language
+(WhyML), and an intermediate representation of logical
+formulaes and goals.
+
+CAISAR supports the verification of multiple machine learning programs.
+Neural Network (NN) are handled through the `ONNX exchange format <https://onnx.ai/>`_.
+Support Vector Machines (SVM) are supported through an ad-hoc CSV format.
+Gradient boosting models and decision trees will soon be
+supported.
 
-You may browse the documentation for :ref:`installation` and :ref:`usage`.
+Provers
+-------
 
+CAISAR heavily relies on external software to provide
+answers on proof obligations. Those programs are called
+"provers", altough some of them may not directly provide a
+logical proof.
 
-Content
-=======
+The supported provers is as follow:
+
+* `PyRAT <https://laiser.frama-c.com/laiser-websites/pyrat-website/>`_,
+  a neural network verifier powered by abstract interpretation (some developers of CAISAR are also working on PyRAT)
+* `Marabou <https://github.com/NeuralNetworkVerification/Marabou>`_, a Satisfiability Modulo Theory (SMT) solver specialized in Neural Network verification
+* `SAVer <https://github.com/abstract-machine-learning/saver>`_, a tool for verifying reachability properties on SVM
+* `nnenum <https://github.com/stanleybak/nnenum>`_
+* "Traditional" SMT solvers that support SMTLIBv2 input
+  language (including `Alt-Ergo <https://alt-ergo.ocamlpro.com/>`_, `Z3 <https://github.com/Z3Prover/z3/wiki>`_, `Colibri <https://colibri.frama-c.com/>`_)
+
+If you would like for CAISAR to support a tool you are
+developping, please reach out so we can discuss about it!
+
+Browse the documentation
+------------------------
+
+Installation instructions for CAISAR are available at :ref:`installation`.
+A description of core usage is available at :ref:`usage`.
+Finally, we provide some :ref:`examples` as well.
 
 .. toctree::
    :maxdepth: 3
-   :caption: Contents
 
    installation
    usage
    examples
-
-
-..
-   Indices and tables
-   ==================
-   * :ref:`search`
diff --git a/doc/modules.rst b/doc/modules.rst
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-API documentation
-=================
-
-To be generated with odoc.
-
-.. toctree::
-   :maxdepth: 4
-
-   nier_cfg